Multi-Scale Computational Modeling Core (MCM)

摘要 多尺度计算建模(MCM)核心将继续提供基本的专业知识和 生物工程的多尺度和多学科计算模拟领域的基础设施 生物医学问题，新增人工智能/机器学习(AI/ML)功能 Cobre阶段II中的数据驱动建模。虚拟人体试验的关键，SC-TRIMH的组织概念， 是开发人体的预测性多尺度模型，以评估新的干预措施、设备和 治疗学。作为其主要任务，该核心将支持我们的SC-TRIMH调查人员的所有计算和 改善肌肉骨骼在分子、细胞、组织、身体和人群水平上的模拟需求 健康。此外，它还将为SC-TRIMH的所有调查人员和同事提供指导和战略规划， 尤其是那些在多尺度计算建模、AI/ML、 或者使用集群并行计算来最大化它们的计算结果。因此，调查人员将被建议 关于充分利用克莱姆森的最佳方法、模型构建策略和软件设置 大学的集群并行计算能力和广泛的AI/ML研究能力。此外，我们还将 努力将MCM核心打造成促进全面计算生物工程的“首选之地” 为南卡罗来纳州、东南部、全国和世界各地的调查人员进行的研究。 具体地说，MCM核心将维护和开发最先进的软件工具和包，以实现 SC-TRIMH研究人员将在分子、细胞、 组织、身体和种群水平(目标1)；MCM核心将调整和扩展当前的计算集 集成基于AI/ML的建模的工具和包，以便在Clemson的Palmetto集群(AIM)上运行 2)；MCM核心将加强对Cobre Research的标准和具体项目的援助和指导 项目负责人(RPL)、其他SC-TRIMH调查人员和他们的团队，特别是那些没有主要 在复杂问题建模方面的专门知识(目标3)；MCM核心将进一步推动MCM核心成为 领先的资源和来自东南部南卡罗来纳州克莱姆森大学的研究人员的首选之地 区域和区域以外的所有多尺度和多学科的复杂生物工程和 细胞、组织、身体和人群层面的生物医学问题，特别强调构建 针对特定患者或基于队列的肌肉骨骼系统(目标4)。自MCM核心问世以来， 利用核心技术的项目数量每年都有显著增加。在第二阶段，我们将进一步 通过获取和开发基于AI/ML的新软件工具和包来发展核心能力 建模及其与确定性建模和概率建模的集成。养成肌肉骨骼 研究社区，我们将扩展现有平台，增强SC-TRIMH之间的互动 与计算建模相关的研究人员、核心主管和外部资源。

SUMMARY The Multi-scale Computational Modeling (MCM) Core will continue to provide essential expertise and infrastructure in the area of multi-scale and multi-discipline computational modeling of bioengineering and biomedical problems, with a new addition of Artificial Intelligence/Machine Learning (AI/ML) capacities for big data driven modeling in the COBRE Phase II. Key to Virtual Human Trials, the organizing concept of SC-TRIMH, is to develop predictive multi-scale models of the human body for assessing new interventions, devices, and therapeutics. As its main mission, this core will support our SC-TRIMH investigators in all their computation and simulation needs at molecular, cellular, tissue, body, and population levels toward improving musculoskeletal health. Additionally, it will provide mentoring and strategic planning to all SC-TRIMH investigators and associates, especially those who do not have primary expertise in the areas of multi-scale computational modeling, AI/ML, or using cluster parallel computing to maximize their computational outcome. Thus, investigators will be advised on best approaches, model building strategies, and software settings to take full advantage of Clemson University's cluster parallel computing capabilities and extensive AI/ML research capacity. Furthermore, we will strive to build the MCM Core into the “go-to place” that facilitates comprehensive computational bioengineering research for investigators from across South Carolina, in the southeast, the nation, and around the world. Specifically, the MCM core will maintain and develop the most advanced software tools and packages to enable SC-TRIMH investigators to perform computational bioengineering and biomedical modeling at molecular, cellular, tissue, body, and population levels (Aim 1); the MCM core will tune and expand the current set of computational tools and packages to integrate AI/ML based modeling so that they will run on Clemson's Palmetto Cluster (Aim 2); the MCM core will enhance standard and project-specific assistance and mentoring to the COBRE Research Project Leaders (RPLs), other SC-TRIMH investigators, and their team, especially those who do not have primary expertise in modeling of complex problems (Aim 3); the MCM core will further promote the MCM Core as a leading resource and the “go-to place” for researchers from Clemson University, South Carolina, the southeast region and beyond for all multi-scale and multi-discipline computational modeling of complex bioengineering and biomedical problems at cellular, tissue, body, and population levels with special emphasis on expertise in building patient-specific or cohort-based musculoskeletal systems (Aim 4). Since the inception of the MCM core, the number of projects utilizing the Core has significantly increased each year. During Phase II, we will further develop the core capacities by acquisition and development of new software tools and packages for AI/ML-based modeling and its integration with deterministic modeling and probabilistic modeling. To nurture a musculoskeletal research community, we will expand the current platform to enhance the interaction between the SC-TRIMH investigators, Core Directors, and external resources relating to computational modeling.